HiLo-RD improves low-budget masked diffusion language models
Self-distillation from large-window states raises GSM8K accuracy by 9.4 points and cuts mean readable length by about 25%.
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Stories tagged #masked-diffusion
IDRF: Inverse-Distilled Reward Fine-tuning of Masked Discrete Diffusion Models
IDRF reward-fine-tunes few-step masked discrete diffusion models via inverse-distillation regularization, achieving high reward with up to 32x fewer denoising steps while mitigating reward hacking.
E-MoE: Enhanced Mixture-of-Experts for Non-Factorized Diffusion Language Models
E-MoE adds a discrete MoE latent to diffusion language models and improves few-step generation.
TANGO: Watermarking Masked Diffusion Language Models in Token Pairs
TANGO watermarks masked diffusion language models via token pairs, resisting frequency attacks that forge fixed green lists.
Unmask the State: When Does State Adaptation Matter for Masked Diffusion Language Models
Selective state adaptation captures most masked-diffusion gains, including 56.9% of LLaDA-8B oracle opportunity.
Schedule optimization for tau-leaping in masked discrete diffusion
A theory paper derives optimal denoising schedules for tau-leaping samplers in masked discrete diffusion models.
Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model
Dynin-Robotics omnimodal diffusion vision-language-action model unifies action, dynamics, and goal prediction, reaching 78.4% success on Franka tasks.
Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model
Dynin-Robotics unifies action, goal, and dynamics prediction in one omnimodal masked-diffusion VLA model, reaching 78.4% success on Franka Research 3 manipulation tasks.
H Company Releases NeoMME: A Family of 260M and 800M Single-Tower Multimodal Encoders That Drop the Vision Tower and Causal Decoder
H Company released NeoMME, 260M/800M single-tower multimodal encoders matching 3.75B ColQwen2.5 on ViDoRe v3 while being 14.4x smaller, under Apache 2.0.
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